2022-06-21, 11:45–12:15, Room 1
While academic research heavily depends on open-source software, the relationship is often one-way. We believe that designing research in close relation to open-source development is beneficial for all parties and present one way of doing that, by turning a research project into a component of the open-source ecosystem.
Academic research often depends on open-source software. Still, researchers do not contribute back that often due to the lack of institutional incentives, time demands, or an imposter syndrome (“my code is too messy”). However, open-source software development doesn’t have to be detached from academic work.
The first step is a decision to make the code open. Then the question is, how?
From an academic standpoint, packing up the functionality into a new package instead of contributing to existing libraries could lead to additional publications that matter in career progress. However, from an open-source standpoint, such an approach widens the ecosystem’s fragmentation and threatens its sustainability. In this talk, we outline why we chose the path benefiting open source over the academic benefits, how we did it and our vision of academic work closely linked to open-source development.
We illustrate this approach in our work on the Urban Grammar AI project, combining aspects of radical openness of the process, making research code available as it is written, and enhancing existing libraries when we need new functionality. It led to significant contributions to the GeoPandas and PySAL ecosystem, a release of one independent package with functionality that didn’t fit elsewhere, and further developments of a canonical Docker container for geographic data science.